A robust optimization framework for forest biorefineries design considering uncertainties on biomass growth and product selling prices

The dependence of biomass growth on uncontrolled environmental factors and the lack of confidence in product selling price estimation imposes challenges for the efficient design of biorefineries, especially for forest systems, which present complex and long-termed growth behavior. The present work proposes the expansion of an optimization framework for forest biorefineries design to handle uncertainties on both biomass productivity and product selling prices. A robust formulation is proposed under a box and polyhedral uncertainty set formulation allowing its conservatism degree to be controlled. A case study of a eucalyptus biorefinery in Brazil illustrates the model's capabilities. The canonical worst-case approach to uncertainties on selling prices leads to a null optimal Net Present Value (NPV) and, on biomass growth, leads to a design that uses a 70% excess of lands. Scenarios of a controlled degree of conservatism lead to designs closer to the uncertainty-free optimal NPV of 136 bi BRL.